Published on: July 2026
TOPOLOGICAL ANALYSIS OF DIABETES MELLITUS DRUGS USING GRAPH THEORY, LINEAR REGRESSION MODELS, AND PREDICTIVE MACHINE LEARNING SUITES
Pavan K R K Abhishek
Near Ravi Shankar Guruji Ashram, Tatguni, Bengaluru, Agara, Karnataka 560082, India
Article Status
Available Documents
Abstract
KEYWORDS: QSPR analysis, Linear Regression, XGBoost, Support Vector Regression, DLF index, Antidiabetic Drugs.
How to Cite this Paper
R, P. K. & Abhishek, K. (2026). Topological Analysis of Diabetes Mellitus Drugs Using Graph Theory, Linear Regression Models, and Predictive Machine Learning Suites. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(7), 1-9. https://doi.org/10.55041/ijcope.v2i7.180
R, Pavan, and K Abhishek. "Topological Analysis of Diabetes Mellitus Drugs Using Graph Theory, Linear Regression Models, and Predictive Machine Learning Suites." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 7, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i7.180.
R, Pavan, and K Abhishek. "Topological Analysis of Diabetes Mellitus Drugs Using Graph Theory, Linear Regression Models, and Predictive Machine Learning Suites." International Journal of Creative and Open Research in Engineering and Management 02, no. 7 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i7.180.
References
[1] Ahmed, W., Zaman, S., Asif, E., Ali, K., Mahmoud, E. E., & Asheboss, M. A. (2024). Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms. BMC Chemistry, 18, 167.[2] Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5-32.
[3] Chen, T., & Guestrin, C. (2016). XGBoost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 785-794).
[4] Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), 273-297.
[5] Genitsaridi, I., Salpea, P., Salim, A., Sajjadi, S. F., Tomic, D., James, S., Thirunavukkarasu, S., Issaka, A., Chen, L., Basit, A., Luk, A. O. Of the IDF Diabetes Atlas: global, regional, and national diabetes prevalence estimates for 2024 and projections for 2050. The Lancet Diabetes & Endocrinology, 2026, 14(2), 149-156.
[6] Kuriachan, G., & Angamuthu, P. (2026). Ranking Antidiabetic Drugs Using a Multi-criteria Decision-making Approach Based on Domination Distance-based Topological Indices and QSPR Modeling. Current Organic Synthesis, 23(1).
[7] Montgomery, D. C., Peck, E. A., & Vining, G. G. (2021). Introduction to Linear Regression Analysis. John Wiley & Sons.
[8] Quinlan, J. R. (1986). Induction of decision trees. Machine Learning, 1(1), 81-106.
Ethical Compliance & Review Process
- •All submissions are screened under plagiarism detection.
- •Review follows editorial policy.
- •Authors retain copyright.
- •Peer Review Type: Double-Blind Peer Review
- •Published on: Jul 18 2026
This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.

